AI Briefing#hybrid-search
The latest AI and developer news about #hybrid-search, with the original source and a short summary.
The latest AI and developer news about #hybrid-search, with the original source and a short summary.
Hugging Face has introduced a hybrid search system for Papers with Code that combines PostgreSQL full-text search and pgvector vector search using RRF.
Applying Rerank improves BM25 but degrades performance by up to 9% in hybrid search.
Toss Securities introduces the process of advancing its recommendation and search systems toward real-time personalization and RAG-based architectures.
Revealed the architecture and design decisions for building Papers with Code's hybrid search system using Hugging Face infrastructure.
pgContext, an extension that supports both vector search and hybrid search within PostgreSQL, has been released.
Dongwon F&B leveraged Amazon Bedrock to build an AI agent that goes beyond a simple chatbot to deliver personalized shopping experiences.
Based on Elasticsearch, a hybrid search architecture for agents' long-term memory was designed and its performance was verified.
This case study covers how GloZ uses Amazon OpenSearch and Claude Haiku to transform natural language queries into search DSL and optimize hybrid search.
Reeman Korea built a natural language-based product search system using Amazon Bedrock Knowledge Bases, achieving 95% search accuracy.
GloZ redesigned its search pipeline and indexing for 100,000 resumes using OpenSearch and Bedrock.
AI Search provides vector-keyword hybrid search and per-instance search.
Kurly adopted Google Vertex AI Search to resolve typo and synonym issues, improving purchase conversion by over 300% in no-result (NR) search cases.